Dynamic Bi-Colored Graph Partitioning

In this work, we focus on partitioning dynamic graphs with two types of nodes (bi-colored), though not necessarily bipartite graphs. They commonly appear in communication network applications, e.g., one color being base stations, the other users, and the dynamic process being the varying connection status between base stations and moving users....

Learning Time-Varying Graphs form Online Data

This work proposes an algorithmic framework to learn time-varying graphs from online data. The generality offered by the framework renders it model-independent, i.e., it can be theoretically analyzed in its abstract formulation and then instantiated under a variety of model-dependent graph learning problems. This is possible by phrasing (time...

Online Graph Learning from Time-Varying Structural Equation Models

Topology identification is an important problem across many disciplines, since it reveals pairwise interactions among entities and can be used to interpret graph data. In many scenarios, however, this (unknown) topology is time-varying, rendering the problem even harder. In this paper, we focus on a time-varying version of the structural...

Advanced flooding-based routing protocols for underwater sensor networks

Flooding-based protocols are a reliable solution to deliver packets in underwater sensor networks. However, these protocols potentially involve all the nodes in the forwarding process. Thus, the performance and energy efficiency are not optimal. In this work, we propose some advances of a flooding-based protocol with the goal to improve the...